Remember waiting in a long queue to get movie tickets to finally hear, ‘Sorry, it is houseful!’ or asking numerous people on the way to go to a particular place, taking long roads to find out it is blocked? Well, you can now book tickets with a few clicks, and even better, watch movies on OTT and find the route or see if there are any blockages with just a click of the map. Welcome to the digital world! Over the past few years, the progress we have made in terms of technology has brought us to a world that is convenient, easy, and less chaotic.
Amazon, for instance, is a pioneer in AI with its use of machine learning in logistics, personalized recommendations on its e-commerce platform, and voice AI via Alexa. Amazon has now introduced tools that allow sellers to create high-quality product listings and video ads using generative AI.
This explosion in development is transforming every aspect of our business and life. Artificial Intelligence is one such emergence that has made our day-to-day life so much easier.
So, what does it mean to become AI-native?

What is AI-native business?
Businesses that pervasively make use of Artificial Intelligence in every fabric of their business and thus make AI run the core of their business is an AI-Native business. Unfortunately, the term AI-native is not well defined as we are not there fully yet. But hop on; soon, it will become a reality like any other technology, which has become inevitable.
The Mindset
Consider all spectrums of your business that are under the legacy system and the fundamental approach to doing things. It is practically impossible to become an AI-native business in a go, and it is a conscious decision to actively adopt artificial intelligence for business from the ground up and not just integrate AI as plug-and-play. For an AI-native business, AI becomes the core and seamlessly inherits its brilliance to all frames of business, such as architecture, applications, processes, interactions, infrastructure, and ecosystem. Getting there is more of a cultural mindset of making AI the core than just embedding AI only in frames where it is deemed comfortable.

The Road Ahead
While this looks like a long road, young startups like Orbitshift are already building AI-native solutions. With the growth and limitless opportunities presented by generative AI, AI-native companies have a huge potential to become what internet-native and digital-native companies have become. Some startups that started to build traditional companies are reimagining and restarting to become AI-native startups. Days are not much far where it is assumed that every company has AI at its core and does not need a special mention of AI, just like companies do not mention they are internet-based nowadays.
AI-native businesses are trying to solve problems a hundred times better and faster. These companies envision solutions that are not just better but something that has not existed before.
The Growth of AI
As the role of AI grows, businesses that pick up the adoption fast will have the first-mover advantage in all aspects of business pursuits, just like how digital-native businesses ride their success wave for early adoption of digital initiatives. Generative AI is one such example of businesses that picked up the early adoption of Generative AI, which has already seized opportunities and shown new capabilities that are already ahead of the curve.
A couple of years back, companies that had just scratched the surface of AI but had taken the right steps on their AI journey were seeing a massive growth curve. For those who think AI is capital-intensive, companies like Open AI, and Meta are building general-purpose functional AI solutions, which one can use to see ten or a hundred times better growth, if not a thousand.

These AI-native businesses may vary based on the scale, segments they operate, and the problem space they are trying to solve. More avenues will also open for AI-native businesses to help traditional companies replace and augment AI-native solutions. The advent of Generative AI has created unprecedented opportunities for businesses.
Reimagining traditional business pieces with AI
Easier said than done—how to practically go about achieving this is always a question that ponders every business. From an application and implementation perspective, businesses should identify different layers that form their business and rethink AI as the core of each of them. Some of the business layers are as follows:
- Creating AI training models and ecosystems
- AI safety and control systems
- Interaction between various operations and system
- Architecture
- AI computational power
- Data storage and processing
- MLOps
- Creating an AI execution environment

Understanding the maturity of the company
AI-native implementation ideally requires understanding the maturity of the company. What are the data stacks required to train AI models? What computational and storage needs are required? And so on. AI-native businesses need humongous data and will not depend on just one model; they will have multiple models for the smooth operations of various components of the business. These AI models require strong computing power to develop an efficient system. It also requires robust MLOps to test and ship quality outputs for continuous experimentation and deployment. With these in mind, the maturity of the business and the level of AI readiness have to be gauged.
Implementation
The implementation often starts with replacing an existing identified component, adding a new component, and eventually having fully controlled AI systems. The successful implementation of building AI-native systems means not just doing things more efficiently but bringing innovation to build, create, and augment pathbreaking solutions and platforms.

Final Words
Get ready already!
Companies like Salesforce have reimagined customer relationship management by embedding AI into their core systems with their Einstein Copilot platform. They demonstrated how AI-native solutions can revolutionize traditional B2B workflows, helping companies scale efficiently and stay ahead in competitive markets.
There was a time when businesses were incorporating digital strategies to their businesses to differentiate, which had slowly become a necessity. AI will follow a similar path. Unburden your legacy approach by having AI run the show. We also have to remember that tackling the constraints that come with AI is a learning curve of its own that you hasten up to allow mistakes, experiment, and handle these challenges to become ‘truly AI-native’ before it becomes a rush for necessity.